class_docstr: LIT model API implementation for UMAP.
code: def fit_transform(self, inputs):
      x_input = [i["x"] for i in inputs]
      if not x_input:
          return []
      x_train = np.stack(x_input)
      logging.info("UMAP input x_train: %s", str(x_train.shape))
      zs = self._umap.fit_transform(x_train)
      self._fitted = True
      return ({"z": utils.coerce_real(z)} for z in zs)
  
file_path: lit/lit_nlp/components/umap.py
imports: from absl import logging
  from lit_nlp.api import model
  from lit_nlp.lib import utils
  import numpy
  import umap
label_desc: Use image node_id 2 for calling the UmapModel obj's underlying member method code with example usage: obj.fit_transform(inputs) and returns: unknown, list